Data adaptive ramp in a digital filter
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 US7027498B2 US7027498B2 US09774832 US77483201A US7027498B2 US 7027498 B2 US7027498 B2 US 7027498B2 US 09774832 US09774832 US 09774832 US 77483201 A US77483201 A US 77483201A US 7027498 B2 US7027498 B2 US 7027498B2
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 H03—BASIC ELECTRONIC CIRCUITRY
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Abstract
Description
1. Field of the Invention
The present invention relates to digital systems. More specifically, the present invention relates to digital filters used to control bandwidth in a communication system.
2. Description of the Related Art
Modern communication systems have evolved from using predominantly analog circuitry to predominantly digital circuitry over the past several years. Where there use to be passive and active analog circuits used to oscillate, mix, filter and amplify signals in ‘analog’ domain, there are now digital signal processing circuits that employ specialized microprocessors, DSP's and related circuits to process signals in the digital domain. At the circuit component level, digital circuits are much more complex, employing millions of devices in some circumstances. However, at the device level, digital communications circuits are much simpler, often times using just a handful of devices to accomplish a complex communications task. Portable wireless devices are good examples of this high level of integration. Digital communications circuits also provide the substantial benefit of programmability. A single device can serve many functions over time, allowing the system designer to closely tailor the function of the communications system to the needs of the effort at hand.
One particular functional area that has benefited from the transition to the digital domain is signal filtering. As system designs have become more stringent, with narrowing bandwidths and higher information rates, analog filter topologies had become very complex, expensive, and prone to parts and circuit tolerance limitations. Analog filters become rather poor choices when narrow bands, close channelization, and high information rates force the need for very high order filters to meet system design criteria. Fortunately, the advent of digital signal processing and digital filter theory has alleviated this problem to a great degree. However, digital filters are not without their own limitations, and the state of the art has evolved to the point where even digital filter designs are challenged to meet tight system requirement.
A particular family of filters that is commonly employed in digital communication systems implemented with digital filtering technology is the finite impulse response, or ‘FIR’, filter. These filters are often characterized by linear phase response and constant group delay without feedback. In a typical implementation, a FIR filter response is implemented as a number of taps in a time domain delay line, each tap having an associated coefficient that defines the filter response characteristics. The number of taps indicates the order of the filter, as well as the amount of processor overhead that is required to implement the filter. The implementation of a FIR filter in a digital signal processor is widely understood by those skilled in the art. In fact, commercial software applications exist that allow designers to enter desired filter response parameters and then quickly produce filter tap coefficients that meet the design characteristics. Digital signal processing devices offer low level instructions designed to make filter implementation as efficient as possible.
As is understood by those skilled in the art, digital filters, like any filter, can be represented in the frequency domain or the time domain. In the frequency domain, segments of the filter transfer function are delineated as the pass band, stop band and transition band in a typical highpass, lowpass, or bandpass filter. The frequency domain can be readily transformed to the time domain. In the time domain, the filter response is represented by an impulse function. A filter designed in the frequency domain with a fixed frequency cutoff has a theoretically infinite time impulse response to fully realize the cutoff frequency. Since time is always constrained, the impulse function must be truncated. However, truncating the time domain necessarily results in a broadening, or splattering, of energy bandwidth in the frequency domain. Where a filter is used to control bandwidth, as in channelizing a communications signal, this splattering of energy can result in undesirable interference, noise, reduced system performance, and violation of FCC regulations. The problem is of particular concern in any system where the communications of information must be started and stop with any regularity. A digital filter requires time to ramp up and produce useful output. Thus, there is a period of time at the beginning and end of each transmission block of information which does not contribute to the communications of useful information through the system. In effect, the data throughput performance of the system is compromised by the filter's limitations.
There are certain techniques available to those skilled in the art for controlling this limitation of digital filter systems. One technique is to further truncate the filter at the beginning and ends of transmission periods. This results in reduced system noise immunity and spectral spreading for those periods, but can be employed to advantage none the less. Another technique is to reduce the rampup and rampdown periods for the filter and control the resultant spectral spreading by truncating and windowing the data for the ramp periods. In effect, the energy is forced to zero at the very beginning and ending moments of a time slot of signal transmission. Even given these techniques, the system designer is forced to exchange spectral efficiency for data bandwidth performance in such systems. Thus, there is a need in the art to improve data throughput, by reducing ramp up and ramp down time performance in digital communication filters while maintaining control of spectral performance.
The need in the art is addressed by the systems and methods of the present invention. An apparatus for reducing output energy and bandwidth of an intermittent data stream through a digital filter is disclosed. The apparatus comprises a digital filter and a controller coupled to the digital filter and operable to calculate at least a first ramp data field in accordance with coefficients selected to minimize energy in a truncated tail of the digital filter as a function of at least a first data field. In a refinement of this apparatus, the first data field is adjacent to the ramp data field. In a further refinement, the controller is further operable to window the ramp data field. In a further refinement, the controller is further operable to calculate both of a rampup and a rampdown ramp data field as a function of the at least a first data field and a second data field respectively, and the rampdown coefficients are the mirror image of the rampup coefficients, provided that the digital filter is symmetrical.
Another apparatus is disclosed and serves the purpose of generating coefficients (based on the digital filter tap weights) that are used to calculate ramp symbols. The coefficients are derived by minimizing energy in the at least a first truncated tail data field as a function of at least a first data field, and at least a first ramp data field. At least a first coefficient is derived by setting the partial derivative of the energy of the at least a first truncated tail data field with respect to at least a first ramp data field equal to zero, and solving the equation for the at least a first ramp data field. The coefficient of the at least a first data field in the solution represents the at least a first coefficient in the solution for an arbitrary at least a first data filed. The present invention teaches and claims a method for reducing the energy in the truncated tail of a filter response to a burst data by adaptively calculating ramp symbols as a function of the data input to the digital filter.
A first method comprises the step of calculating at least a first ramp data field in accordance with coefficients selected to minimize energy in a truncated tail of the digital filter as a function of at least a first data field. In a refinement of this method, the at least a first data field is adjacent to the ramp data field. In another refinement, the method also includes the step of windowing the ramp data field. In a further refinement, the calculating step is applied to both of a rampup and a rampdown ramp data field as a function of the at least a first information data field and a second information data field respectively, and wherein rampdown coefficients are the mirror image of the rampup coefficients.
Another method taught by the present invention comprises the steps of calculating the energy in at least a first truncated tail data field as a function of at least a first ramp data field variable and at least a first data field variable, and taking a partial derivative of the energy in the at least a first truncated tail data field with respect to the at least a first ramp data field variable. Then, writing an equality by setting the partial derivative equal to zero, and solving the equality for the at least a first ramp data field variable as a function of the at least a first information data field thereby generating at least a first coefficient. In a refinement of this method, the energy in the at least a first truncated tail data field is also a function of the digital filter tap coefficients.
Illustrative embodiments and exemplary applications will now be described with reference to the accompanying drawings to disclose the advantageous teachings of the present invention. While the present invention is described herein with reference to illustrative embodiments for particular applications, it should be understood that the invention is not limited thereto. Those having ordinary skill in the art and access to the teachings provided herein will recognize additional modifications, applications, and embodiments within the scope thereof and additional fields in which the present invention would be of significant utility.
The preferred embodiment utilizes the present invention in a trunked land mobile radio system that employs FDM channelization and TDMA packetized data for channel trunking management, system control, data communications, and voice communications. Reference is directed to
The terminal units 4 communicate via radio frequency waves (not shown) with base station 1 via antenna 10. Reference is directed to
In the preferred embodiment, the land mobile radio system operates in the US SMR band of frequencies that are allocated by the FCC. Reference is directed to
In the preferred embodiment, the allocated channels are advantageously subdivided to improve capacity as is illustrated in
It should be noted in
A further advantageous use of the radio spectrum within the preferred embodiment is illustrated in
In operation, the terminal units, illustrated as block 4 in
Reference is directed to
Turning off the transmitter for the last three data fields reduces the total number of transmitted data fields to one hundred seventeen 46. The first and last two of these fields, identified as items 50, 52, 54, and 56, are used to ramp up and ramp down the digital filter to control spectral splattering, which concept will be more fully developed hereinafter. Therefore, the data fields remaining for transmission of usable data are one hundred twelve 48, as are indicated by data field numbers three through one hundred fifteen in
The preferred embodiment utilizes a sixteenpoint constellation quadrature amplitude modulation scheme (hereinafter ‘QAM’) for the encoding of data onto the radio frequency carrier. Therefore, each point on the constellation defines one of sixteen data values, which are mapped to fourbit data fields, generally called ‘symbols’ by those skilled in the art. In
Reference is directed to
Mapping circuit 70 produces two digital outputs for the inphase and quadraturephase inputs of the QAM modulator 76, which are coupled to a pair of Nyquist filters 72 and 74. The Nyquist filters are implemented as 65tap finite impulse response (hereinafter ‘FIR’)filters in a DSP in the preferred embodiment. Actually, since a Nyquist filter impulse response is used to reduce inter
symbol interference at the output of the modulator 76, the filters 72 and 74 generate a squareroot Nyquist response output, accomplished mathematically in the DSP. In preparation to modulation in the analog domain, the digital signals output by the squareroot Nyquist filters 72 and 74 are converted to the analog domain by digital to analog converters 71 and 73 respectively. These signals are multiplied in the modulator 76 to produce the desired Nyquist filter response characteristics. Within the modulator 76 is an intermediate frequency (hereinafter ‘IF’) reference oscillator 78 that drives a first mixer 82. The filtered signal from Nyquist filter 72 is thus mixed with the IF in mixer 82. The IF oscillator 78 is also coupled through a 90° phase shift circuit 80, which in turn couples to the second mixer 84. The output of the second Nyquist filter 74 is mixed with the phaseshifted IF signal in mixer 84. The two modulated IF signals are combined in adder 86 and output as a QAM modulated IF signal from modulator 76. Finally, the QAM modulated IF signal is mixed with a signal from a radio frequency (hereinafter ‘RF’) oscillator 90 in mixer 88, which outputs the QAM modulated RF carrier. The RF carrier is coupled to the receiver circuit 60 via channel 92. In the preferred embodiment, the channel 92 is via radio wave propagation.
The receiver circuit 60 in
The advantages of using Nyquist filters in digital communications systems are well understood by those of ordinary skill in the art. With the advent of digital signal processing technology, Nyquist filters are now commonly implemented as digital filters written as software applications for a DSP, ASIC, or FPGA. Many are implemented as multitap FIR filters, often times of the raisedcosine variety. Naturally, along with the advantages of DSP technology and digital filtering, there are certain limitations to be managed as well.
Major objectives of the design of the baseband digital filter system are to choose the transmitting and receiving filters to minimize the effects of noise, eliminate or minimize intersymbol interference and to reduce stop band energy. Intersymbol interference can theoretically be eliminated by proper shaping of the impulse response characteristics of the transmitted signal. See
Modern implementations of pulse shaping filters use a pair of matched filters, one in the transmitter and one in the receiver. The convolution of the transmit filter with the receive filter forms the complete pulse shaping filter. Intersymbol interference is avoided since the combined filter impulse response reaches unity at a single point and is zero periodically at every other information point (the Nyquist symbol/information rate). The linear superposition of pulses representing a pulse train preserves bandwidth and information content. Linear superposition of band limited pulses remains band limited and sampling the combined filter at the information rate at the correct sampling point recovers the information.
Zero crossings of the impulse response function of a Nyquist filter occur at the information rate, except at the one, center, information bearing point. All Nyquist filters having the same stop band are theoretically equally bandwidth limited if the time response is allowed to go to infinity. Realizable filters, however, are truncated in time since it is not possible to have infinitely long impulse responses. With respect to the preferred embodiment, where a TDMA technique is employed, the time domain is even more limited in that the terminal unit transmit energy should be at zero at the beginning and end of each 30 ms transmit window. Truncation error in the time domain causes the theoretical stop band achievable by a Nyquist filter to be violated, so that out of band energy exists in excess of the stop band frequency. A well designed Nyquist filter balances this tradeoff efficiently given system design criteria and the general need to obtain the best possible data performance of the system.
The most efficient filter is the “brick wall” filter illustrated in
To produce a realizable filter, the ideal filter is approximated by time delaying and truncating the infinite impulse response. Truncation, however, produces unintentional out of band energy in excess of the theoretical stop band. One goal that is achieved by the present invention is to minimize this undesirable out of band energy after the filter is truncated.
Attention is directed to
The parameter controlling bandwidth of the raised cosine Nyquist filter is the rolloff factor α. The rolloff factor α is one (α=1) 118 if the ideal low pass filter bandwidth is doubled, that is the stop band goes to zero at twice the bandwidth 2f_{N } 126 (and −2f_{N } 128) of an ideal brick wall filter at f_{N}. If α=0.5 116 a total bandwidth f 1.5f_{N }(not shown) would result, and so on. The lower the value of the rolloff factor α, the more compact the spectrum becomes but the longer time it takes for the impulse response to decay to zero.
In the time domain, referencing
In the preferred embodiment, the Nyquist filter is implemented as a digital filter at a 65 times oversample rate. The truncation length is eight symbol periods long, or sixteen total symbol periods, giving the number of the number of taps as sixteen times sixtyfive, or one thousand twentyfour total taps. The filter is implemented in polyphase form, where the unique data inputs occur at the symbol rate. Polyphase implementation of digital filters is a well known digital technique to those of ordinary skill in the art. Theoretical Nyquist filters are not realizable (since infinite time in both directions is necessary to fully realize the theoretical stop band properties of the filter). Practical Nyquist filters are made by time delaying and truncating the infinite impulse response. After choosing the a factor, the oversample rate (65) and the number of symbol time delays for the filter to realize the symbol value (8), fully specifies the filter tap values for the example raised cosine class of filters.
Given the digital filter design and the eight period decay time, out of band energy is naturally controlled to the filter's digital/truncation limit, according to the α factor selected in the design. However, since the filter operates in a TDMA system, it must ramp up and ramp down during every 30 ms TDM slot interval. In a pulse shaping filter, the filter is normally initialized with zeros, and the natural ramp up takes a delay of eight (in this instance) symbols to realize the first information point. The natural ramp down also takes eight zeros (at the sampling rate) to ramp the filter down in a spectrally efficient way. Sacrificing eight leading and eight trailing symbol periods in a 120 symbol slot interval to control bandwidth is undesirably wasteful of system and information data bandwidth. One way to improve the efficiency of the design is to truncate the eight symbol periods to a lesser number of symbol periods at the beginning and end of a slot. In the preferred embodiment, the ramp times are truncated to two symbol periods for both the rampup and rampdown periods. The effect of truncating these periods is to generate out of band spectral energy splatter. The present invention reduces this splatter while preserving the data bandwidth efficiency.
The assignee of the present invention has already filed a copending patent pplication for an improved Nyquist filter design. The application is Ser. No. 09/302,078 and entitled IMPROVED NYQUIST FILTER AND METHOD, which was filed in the US Patent Office on Apr. 28, 1999, the contents of which are hereby incorporated by reference thereto.
Reference is directed to
The preferred embodiment digital filter operates on fourbit symbols with an over sampling rate of sixtyfive times. A modified Nyquist filter is employed and the time domain impulse curve is such that eight data symbols is sufficient to provide adequate guard band splatter control. However, for protocol efficiency, the prior art filter utilizes two zerovalued rampup and rampdown data fields with windowing to more quickly ramp the filter and allow for twelve additional useful data symbol periods.
The truncated rampup tail 142 is comprised of data symbols Q1, Q2, Q3, Q4, Q5, Q6, Q7, and Q8. Similarly, the truncated rampdown tail 144 comprises symbols Q8, Q7, Q6, Q5, Q4, Q3, Q2, and Q1. The ramp symbols do not carry useful data. In the present invention, the first six data symbols 148 and the last six data symbols 150 (identified as symbols S3, S4, S5, S6, S7, and S8 in
The present invention improves upon not only the nonwindowed ramp, but the windowed ramp as well, by adapting the ramp symbol values to the transmitted symbol data. The energy in the truncated tail can be minimized and spectral splatter attenuated. A descriptive and mathematical analysis of this approach follows. Reference is directed again to
In the preferred embodiment, the total energy in the tail can be written using the first eight symbols periods (and last eight symbol periods). Of course, in other filter designs, the number of periods may vary as well as the over sampling rate, as is understood by those of ordinary skill in the art. At 65 times over sampling, the magnitudes of each sample point in the truncated tail portion 142 is contained in one of the following vectors, (where Q_{x }is the symbol period of data points, R_{x }(or S_{x}) is the symbol value of the corresponding transmitted data, and h_{y }is the filter tap, or coefficient, value.
The first truncated symbol period sample data output is determined by the first 65 data sample points:
The second truncated symbol period sample data output is determined by the next 65 data sample points:
The third truncated symbol period sample data output is determined by the third 65 data sample points:
The fourth truncated symbol period sample data output is determined by the fourth 65 data sample points:
The fifth truncated symbol period sample data output is determined by the fifth 65 data sample points:
The sixth truncated symbol period sample data output is determined by the sixth 65 data sample points:
The seventh truncated symbol period sample data output is determined by the seventh 65 data sample points:
The eighth truncated symbol period sample data output is determined by the eighth 65 data sample points:
The sum of the squares for each of the sixtyfive sample points of the eight truncated symbol periods indicates the total energy in the truncated tail as follows:
The ramp up symbol values are calculated by solving the least squares to minimize the amount of energy in the truncated tail symbols. The partial derivative of the energy with respect to the two ramp symbols are taken to accomplish this step, as follows:
For clarity and simplicity, the individual terms contributing to the energy in R_{1 }and R_{2 }in the above equations with respect to each vector are individually expressed, and appear below for both R_{1 }and R_{2 }for each term of Equations Eq. 10 and Eq. 11.
First term for Eq. 10 and Eq. 11 respectively:
as there is no R_{2 }argument in the first term.
Second term for Eq. 10 and Eq. 11 respectively:
Third term for Eq. 10 and Eq. 11 respectively:
Fourth term for Eq. 10 and Eq. 11 respectively:
Fifth term for Eq. 10 and Eq. 11 respectively:
Sixth term for Eq. 10 and Eq. 11 respectively:
Seventh term for Eq. 10 and Eq. 11 respectively:
Eighth term for Eq. 10 and Eq. 11 respectively:
The sum of all derivative terms is zero, giving two equations and two unknowns, for the least squares. The sample points are summed and organized to yield the following:
Which is simplified by setting a variable equal to the summation terms, and rewritten as:
α_{11} R _{1}+α_{12} R _{2} =−c _{11} S _{3} −c _{12} S _{4} −c _{13} S _{5 } −c _{14} S _{6} −c _{15} S _{7} −c _{16} S _{8} Eq.30
and
α_{12} R _{1}+α_{22} R _{2} =−c _{21} S _{3} −c _{22} S _{4} −c _{23} S _{5 } −c _{24} S _{6} −c _{25} S _{7} −c _{26} S _{8} Eq.31
Solving for R_{1 }and R_{2 }and converting to matrix mathematics yields:
And defining c′_{xy}=−c_{xy }we have:
Substituting b_{xy }for like elements in the a_{xy} ^{−1 }matrix produces Equation 35 below:
This solution can be calculated in the conventional manner. Thus, a set of coefficients can be generated, based on the filter tap coefficients, and stored in a lookup table for use in calculating the rampup (and rampdown) symbols that yield the lowest energy in the truncated tails. Ramp down is the mirror image of ramp up, given filter symmetry.
In operation, as each TDMA data packet is received, the first and last six valid data packets (items 148 and 150 in
The improvement is apparent upon review of
Filters as described herein can be used in a variety of applications. For example, the filters can be used in any system that utilizes pulse shaping filters. Digital communication systems provide one such example. Filters of the present invention could be used in wireless communications (cellular, GSM, microwave, satellite), wired communications (in telephone systems, cable modems), optical systems, broadcast systems (digital television, digital radio, satellite), and others.
Thus, the present invention has been described herein with reference to a particular embodiment for a particular application. It is therefore intended by the appended claims to cover any and all such applications, modifications and embodiments within the scope of the present invention.
Accordingly,
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US20040047430A1 (en) *  19990428  20040311  Mccarty Robert Joseph  Nyquist filter and method 
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